Table 5.

Results from the empirical example

	LD		JOMO		BLIMP		MDMB
Parameter	Est.	SE	Est.	SE	Est.	SE	Est.	SE
Intercept (β0)	-0.048	0.054	-0.171**	0.053	-0.173**	0.053	-0.202***	0.052
Level 1
Mood (β1)	0.576***	0.128	0.737***	0.138	0.715***	0.145	0.621***	0.138
Stress (β2)	-0.084*	0.042	-0.078	0.044	-0.074	0.045	-0.076	0.042
Mood × Stress (β3)	0.381**	0.144	0.470**	0.152	0.489**	0.166	0.428**	0.151
Level 2
Mood (β4)	1.933***	0.223	1.568***	0.235	1.650***	0.233	1.579***	0.216
Stress (β5)	0.183	0.201	0.242	0.204	0.244	0.206	0.082	0.204
Gender (β6)	0.570***	0.069	0.559***	0.068	0.553***	0.068	0.548***	0.067
Age (β7)	0.014***	0.004	0.015***	0.004	0.015***	0.004	0.015***	0.004
Mood × Stress (β8)	0.780**	0.254	0.688**	0.257	0.711**	0.258	0.645*	0.253
Mood × Gender (β9)	-0.015	0.264	0.086	0.268	0.079	0.267	0.058	0.266
Stress × Gender (β10)	1.728***	0.393	1.941***	0.473	2.321***	0.479	1.604***	0.468
Gender × Age (β11)	-0.001	0.005	-0.000	0.005	-0.000	0.005	0.000	0.005
Cross-level effectsa
Mood × Stress (β12)	0.275*	0.136	0.422**	0.152	0.435**	0.164	0.408**	0.154
Mood × Gender (β13)	-0.075	0.056	-0.098	0.059	-0.085	0.061	-0.086	0.056
Stress × Mood (β14)	0.549*	0.262	0.611*	0.308	0.724*	0.323	0.481	0.305
Stress × Gender (β15)	0.196	0.116	0.297*	0.139	0.114	0.138	-0.130	0.108
Variance components
Intercept (${\tau }_0^2$)	1.535		1.390		1.396		1.398
Slope (Mood, ${\tau }_1^2$)	1.535		1.399		1.801		1.106
Residual (σ2)	1.659		1.797		1.785		1.823

^∗p < .05, ^∗∗p < .01, ^∗∗∗p < .001 (two-sided)

^a For the cross-level effects, level 1 variables are named first (before the “×”) and level 2 variables second (after the “×”)

Note. LD = listwise deletion; JOMO = substantive-model-compatible multilevel MI (joint modeling); BLIMP = substantive-model-compatible multilevel MI (fully conditional specification); MDMB = substantive-model-compatible multilevel MI (sequential modeling)